Tag: Environment and public infrastructure

Environmental Policy in Eastern Europe | SITE Development Day 2021

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The need for urgent climate action and energy transformation away from fossil fuels is widely acknowledged. Yet, current country plans for emission reductions do not reach the requirements to contain global warming under 2°C. What is worse, there is even reasonable doubt about the commitment to said plans given recent history and existing future investment plans into fossil fuel extraction and infrastructure development.  This policy brief shortly summarizes the presentations and discussions at the SITE Development Day Conference, held on December 8, 2021, focusing on climate change policies and the challenge of a green energy transition in Eastern Europe.

Climate Policy in Russia

The first section of the conference was devoted to environmental policy in Russia. As Russia is one of the largest exporters of fossil fuel in the world, its policies carry particular importance in the context of global warming.

The head of climate and green energy at the Center for Strategic Research in Moscow, Irina Pominova, gave an account of Russia’s current situation and trends. Similar to all former Soviet Union countries, as seen in Figure 1, Russia had a sharp decrease in greenhouse gas emissions (hereinafter referred to as GHG emissions) during the early 90s due to the dramatic drop in production following the collapse of the Soviet Union. Since then, the level has stabilized, and today Russia contributes to about 5% of the total GHG emissions globally. The primary source of GHG emissions in Russia comes from the energy sector, mainly natural gas but also oil and coal. The abundance of fossil fuels has also hampered investments in renewable resources, constituting only about 3% of the energy balance, compared to the global average of 10%

Figure 1. Annual greenhouse gas emissions per capita

Note: Greenhouse gas emissions are expressed in metric tons of CO2 equivalents. Source: Emissions Database for Global Atmospheric Research (EDGAR).

Pominova noted that it is a massive challenge for the country to reach global energy transformation targets since the energy sector accounts for over 20% of national GDP and 28% of the federal budget. Yet, on a positive note, the number of enacted climate policies has accelerated since Russia signed the Paris Agreement in 2019. One notable example is the federal law on the limitation of GHG emissions. This law will be enforced from the end of 2021 and will impose reporting requirements for the country’s largest emitters. The country’s current national climate target for 2030 is to decrease GHG emissions by 30% compared to the 1990 level. As shown in Figure 1, this would imply roughly a 10 percent reduction from today’s levels given the substantial drop in emissions in the 1990’s.

Natalya Volchkova, Policy Director at CEFIR in Moscow, discussed energy intensity and the vital role it fills in Russia’s environmental transition. Energy intensity measures an economy’s energy efficiency and is defined as units of energy per unit of GDP produced. Volchkova emphasized that to facilitate growth in an environmentally sustainable way it is key to invest in technology that improves energy efficiency. Several regulatory policy tools are in place to promote such improvements like bottom-line energy efficiency requirements, sectoral regulation, and bans on energy-inefficient technologies. Yet, more is needed, and a system for codification and certification of the most environmentally friendly technologies is among further reforms under consideration.

As a Senior Program Manager at SIDA, Jan Johansson provided insights on this issue from an international perspective. Johansson gave an overview of SIDA’s cooperation with Russia in supporting and promoting environmental and climate policies in the country. The main financial vehicle of Swedish support to Russia with respect to environmental policy has been a multilateral trust fund established in 2002 under the European Union (EU) Northern Dimension Environmental Partnership (NDEP). One of the primary objectives of the cooperation has been to improve the environment in the Baltic and Barents Seas Region of the Northern Dimension Area. Over 30 NDEP projects in Russia and Belarus have been approved for financing so far. Seventeen of those have been completed, and the vast majority have focused on improving the wastewater treatment sector.

Johansson also shed light on the differences that can exist between governments in their approach to environmental policy. For example, in the area of solid waste management, Russia prefers large-scale solutions such as landfills and ample sorting facilities. In Sweden and Western Europe, governments have a more holistic view founded on spreading awareness in the population, recycling, corporate responsibility, and sorting at the source.

Environmental Transition in Eastern Europe

In the second part of the conference environmental policies and energy transformation in several other countries in the region were discussed.

Norberto Pignatti, Associate Professor and Centre Director at ISET Policy Institute, talked about the potential for a sustainable energy sector and current environmental challenges in Georgia. The country is endowed with an abundance of rivers and sun exposure, making it a well-suited environment for establishing the production of renewable energy such as wind, solar, and hydro. As much as 95 % of domestic energy production comes from renewable sources. Yet, domestic energy production only accounts for 21% of the country’s total consumption, and 58% of imported energy comes from natural gas and 33% from coal. Furthermore, the capacity of renewable energy sources has declined over the last ten years, and particularly so for biofuel due to the mismanagement of forests. A notable obstacle Georgia faces in its environmental transition is attracting investors. Low transparency and inclusiveness from the government in discussions about environmental policy, along with inaccurate information from the media, has led to a low public willingness to pay for such projects. Apart from measures to overcome the challenges mentioned, the government is currently working on a plan to impose emission targets on specific sectors, invest in energy efficiency and infrastructure, and support the development of the renewable energy sector.

Like Georgia, Poland is a country where energy consumption is heavily reliant on imports and where coal, oil, and gas stand for most of the energy supply. On top of that, Poland faces significant challenges with air quality and smog and a carbon-intensive energy sector. On the positive end, Poland established a government-industry collaboration in September 2021, that recognizes offshore wind as the primary strategic direction of the energy transition in Poland. Pawel Wróbel, Founder and Managing Director of BalticWind.EU, explained that the impact of the partnership will be huge in terms of not only energy security but also job creation and smog mitigation. The plan implies the installation of 5.9 GW of offshore wind capacity by 2030 and 11GW by 2040. Wróbel also talked about the EU’s European Green Deal and its instrumental role in accelerating the energy transition in Poland. By combining EU-wide instruments with tailor-made approaches for each of the member states, the Deal targets a 55% reduction in GHG emissions by 2030 through decarbonization, energy efficiency, and expanding renewable energy generation. Michal Myck, Director of CenEA, highlighted the role of social acceptance in accelerating the much-needed energy transition in Poland. In particular, to build political support, there is a crucial need for designing carbon taxes in a way that ensures the protection of vulnerable households from high energy prices.

Adapting to the European Green Deal will also create challenges for countries outside of the EU, especially if a European Carbon Border Adjustment Mechanisms (CBAM) is put in place in 2026 as suggested. Two participants touched on this topic in the context of Belarus and Ukraine respectively. Yauheniya Shershunovic, researcher at BEROC, talked about her research on the economic implications of CBAM in Belarus. It is estimated that the introduction of CBAM can be equivalent to an additional import duty on Belarusian goods equal to 3.4-3.8% for inorganic chemicals and fertilizers, 6.7-13.7% for metals, and 6.5-6.6% for mineral products. Maxim Fedoseenko, Head of Strategic Projects at KSE, shared similar estimations for Ukraine, suggesting that the implementation of CBAM will lead to an annual loss of €396 million for Ukrainian businesses and a decrease in national GDP of 0.08% per year.

An example of Swedish support to strengthen environmental policies in Eastern Europe was presented by Bernardas Padegimas, Team Leader at the Environmental Policy and Strategy Team at the Stockholm Environment Institute. The BiH ESAP 2030+ project is supporting Bosnia and Herzegovina in preparing their environmental strategy. This task is made more challenging by the country’s unique political structure with two to some extent politically autonomous entities (and a district jointly administered by the two), and elites from the three different major ethnic groups having guaranteed a share of power. The project therefore aims to include a broad range of stakeholders in the process, organized into seven different working groups with 659 members on topics ranging from waste management to air quality, climate change and energy. The project also builds capacity in targeted government authorities, raises public awareness of environmental problems, and goes beyond just environmental objectives: mainstreaming gender equality, social equity and poverty reduction. The project is 80 percent finished and will produce a strategy and action plan for the different levels of governance in the country’s political system.  There is also a hope that this process can serve as a model for consensus building around important but at times contentious policy issues more generally in the country.

Public Opinion and Energy Security

Finally, Elena Paltseva, Associate Professor at SITE, and Chloé le Coq, Professor at the University of Paris II Panthéon-Asses (CRED), shared two joint studies relating to the green transition in Europe.

Recent research shows that individual behavioral change has a vital role to play in the fight against climate change, both directly and indirectly through changes in societal attitudes and policies motivated by role models. A precondition for this to happen is a broad public recognition of anthropogenic climate change and its consequences for the environment. The first presentation by Paltseva and Le Coq focused on public perceptions about climate change in Europe (see this FREE policy brief for a detailed account). Using survey data the study explores variation in climate risk perceptions between Western Europe, the non-EU part of Eastern Europe, and Eastern European countries that are EU members. The results show that those living in non-EU Eastern European countries are on average less concerned about climate change. The regional difference can partly be explained by low salience and informativeness of environmental issues in the public discourse in these countries. To support this explanation, they study the impact of extreme weather events on opinions on climate change with the rationale that people who are more aware of climate change risks are less likely to adjust their opinion after experiencing an extreme weather event. They find that the effect of extreme weather events is higher in countries with less independent media and fewer climate-related legislative efforts, suggesting that the political salience of the environment and the credibility of public messages affects individuals’ perceptions of climate change risks.

The second presentation concerned energy security in the EU, and the impact of the environmental transition. It was argued that natural gas will play an important role in Europe’s green transition for two reasons. First, since the transition implies a higher reliance on intermittent renewable energy sources, there will be an increased need for use of gas-fired power plants to strengthen the supply reliability. Second, the electrification of the economy along with the phasing out of coal, oil, and nuclear generation plants will increase the energy demand. Today, about 20% of EU’s electricity comes from natural gas and 90% of that gas comes from outside EU, with 43% coming from Russia. To emphasize what issues can arise when the EU relies heavily on external suppliers, the presentation discussed a Risky External Energy Supply Index (Le Coq and Paltseva, 2009) that considers the short-term impact of energy supply disruptions. This index assesses not only the importance of the energy type used by a country but also access to different energy suppliers (risk diversification). The index illustrates that natural gas is riskier than oil or coal since natural gas importers in the EU depend to a greater extent on a single or few suppliers. Another crucial component of the security of gas supplies arises from the fact that 77% of EU’s net gas imports arrive through pipelines, which creates an additional risk of transit. Here, the introduction of new gas transit routes (from already existing suppliers) may increase diversification and decrease risks to the countries having direct access to the new route. At the same time, countries that share other pipelines with countries that now have direct access may lose bargaining power vis-à-vis the gas supplier in question, as demand through those pipelines could fall. Le Coq illustrated this point applying the Transit Risk Index developed in Le Coq and Paltseva (2012) to the introduction of the North Stream 1 pipeline. She concluded that the green transition and associated increase in demand for natural gas is likely to be associated with higher reliance on large gas producers, such as Russia, and resulting in energy security risks and imbalance in the EU. One way to counteract this effect is to exercise EU’s buyer power vis-a-vis Russia within the EU common energy policy. While long discussed, this policy has not been fully implemented so far.

Concluding Remarks

This year’s SITE Development Day conference gave us an opportunity to highlight yet another key issue, not only for Eastern Europe, but for the whole world: global warming and energy transformation. Experts from across the region, and policymakers and scholars based in Sweden, offered their perspectives on the challenges that lie ahead, but also highlighted initiatives and investments hopefully leading the way towards a brighter future.

List of Participants

  • Chloé Le Coq, Professor of Economics at the University of Paris II Panthéon-Assas (CRED). Paris, France. Research Fellow at SITE.
  • Maxim Fedoseenko, Head of Strategic Projects at KSE Institute. Kyiv, Ukraine.
  • Jan Johansson, Senior Program Manager, SIDA. Stockholm, Sweden.
  • Michal Myck, Director of CenEA. Szczecin, Poland.
  • Bernardas Padegimas, Team Leader: Environmental Policy and Strategy, Stockholm Environmental Institute. Stockholm, Sweden.
  • Elena Paltseva, Associate Professor, SITE/SSE/NES. Stockholm, Sweden
  • Norberto Pignatti, Associate Professor of Policy at ISET-PI, and Head of the Energy and Environmental Policy Institute at ISET-PI. Tbisili, Georgia.
  • Irina Pominova, Head of Climatwe and Green Energy at the Center for Strategic Research. Moscow, Russia.
  • Yauheniya Shershunovic, Researcher at BEROC, Minsk, Belarus. PhD Candidate at the Center for Development Research (ZEF). Uni Bonn.
  • Natalya Volchkova, Policy Director at CEFIR, Assistant Professor at the New Economic School (NES). Moscow, Russia.
  • Pawel Wróbel, Founder and Managing Director of BalticWind.EU. Poland.
  • Julius Andersson, Researcher at SITE. Stockholm, Sweden.
  • Anders Olofsgård, Associate Professor and Deputy Director at SITE. Stockholm, Sweden.

Preferences for Redistribution in Post-Communist Countries

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Public attitudes toward inequality and the demand for redistribution can often play an import role in terms of shaping social policy. The literature on determinants of the demand for redistribution, both theoretical and empirical, is extensive (e.g., Meltzer and Richard 1981, Alesina and Angelotos 2005).  Usually, due to data limitations, transition countries are usually considered to be a homogeneous group in empirical papers on the demand for redistribution. However, new data on transition countries allow us to look more deeply into the variation within this group, and to look at which factors are likely to play a significant role in shaping a society’s preferences over redistribution.

The data we use are from the second round of the EBRD and WB Life in Transition Survey (LiTS) (EBRD Transition Report 2011). This is a survey of nationally representative samples consisting of at least 1000 individuals in each of the 29 transition countries.[1] In addition, and for comparison purposes, this survey also covers Turkey, France, Germany, Italy, Sweden and UK. Furthermore, in six of the countries surveyed – Poland, Russia, Serbia, Ukraine, Uzbekistan and UK – the sample consists of 1500 individuals.

Redistribution is, in general, a complex issue, which can take various forms and rely on different mechanisms. In this policy brief, we will only focus on two forms of public attitudes towards redistribution. The first is direct income redistribution from the rich to the poor and public preferences for or against this form of redistribution. The second is indirect redistribution through the provision of public goods, some of which favor certain groups of population over others. In particular, we will consider preferences over extra government spending allocations in the areas of education, healthcare, pensions, housing, environment and public infrastructure. Generally, we would like to explore in greater detail to what extent there are differences across countries in terms of public preferences over redistribution and what might explain differences both within and across societies.

Both survey rounds include questions regarding public preferences towards income redistribution, direct (from the rich to the poor) and indirect (through government spending towards certain public goods). Data for exploring public preferences for direct redistribution can be obtained from a question in the survey that asks respondents to score from 1 to 10 whether they prefer more income inequality or less. More specifically, in the LiTS 2010, the question is the following:

Q 3.16a “How would you place your views on this scale: 1 means that you agree completely with the statement on the left “Incomes should be made more equal”; 10 means that you agree with the statement on the right “We need larger income differences as incentives for individual effort”; and if your views fall somewhere in between, you can choose any number in between?

Note, however, that we use the reverse of this so that 10 represents greater equality and 1 represents wider differences. Bearing this in mind, figure 1 shows the average scores for redistribution preferences for a selection of the countries for 2010 and shows a sizeable variation ranging from 4.4 (more inequality) in Bulgaria to 7.87 (greater equality) in Slovenia. The mean for Russia is 6.92.

The data also allows for a comparison to be made between these preferences in transition countries and in the developed economies covered in the survey. For instance, Russians are on average close to Germans in their preferences for redistribution, while Estonians and Belarusians prefer less redistribution and are closer to the British, on average.

Figure 1. Preferences for Direct Redistribution

Indirect measures of attitudes towards redistribution can add further depth to these societies’ preferences. In particular, the indirect measures in the 2010 survey are derived from a question that asks respondents to rate from 1 to 7 their first priorities for extra government spending.

Q 3.05a “In your opinion, which of these fields should be the first priority for extra government spending: Education; Healthcare; Housing; Pensions; Assisting the poor; Environment (including water quality); Public infrastructures (public transport, roads, etc.); Other (specify)”?

The country averages for these indirect measures for 2010 are presented in Figure 2. The graph reveals a sizeable cross-country variation. For instance, 43.5% of respondents in Mongolia preferred channeling extra government money to education, while 48.7% of respondents in Armenia selected higher healthcare spending. Almost 39% of respondents in Azerbaijan chose assistance to the poor as the first priority for government spending, while the corresponding figure was only 8.3% in Bulgaria and 4% in the Czech Republic. More than 34% of the Russians choose healthcare as their first priority, another 20% choose education, 15% would like the money to be channeled to housing, 14.5% to pensions, 11% to support the poor, 3% to support environment, and only 2% to public infrastructure (2010).

These numbers highlight that there are sizeable differences across the transition countries regarding preferences for redistribution. Also, regarding the form of indirect redistribution in terms of preferences over how government budgets should be prioritized and allocated. Several groups of factors or determinants are typically listed in academic literature to help explain what drives public preferences over the degree and form of redistribution. In the first group of factors, there are various determinants at the individual level. Within the group of individual determinants, self-interest or rational choice of a degree of redistribution favorable to the individual with usual (individual) preferences are stressed. Alternatively, motives behind a preference for redistribution can be related to social preferences (preferences for justice or equity) and reciprocity. Within this general group of self-interest, attitudes towards risks can be stressed as a crucial factor behind demands for social insurance and hence for indirect forms of redistribution. Individuals’ prospects of upward mobility, expectations about their future welfare or ‘tunnel effect’ in shaping their views and preferences over redistribution are also underlined. Also, the commonly held beliefs about the causes of prosperity and poverty are considered to be important in shaping the public’s attitudes under the umbrella of social preferences.

The literature covers possible institutional determinants for preferences towards redistribution and emphasizes the role of the level of inequality in a society and typically relates to the median voter hypothesis in democracies.  It is also stressed that welfare regimes (liberal, conservative) can play a role in shaping the level of public support for redistribution.

Figure 2. Preferences for Indirect Redistribution

A closer examination of the data and estimates of the factors shaping individuals preferences over redistribution in the 2010 survey, are consistent with motives involving strong self-interests of the respondents.[2] Those from richer households have less support for redistribution, with the result being robust to the measure of household income used. The past trend in household income positions is insignificant, while the higher the expected income position of household in the coming four years, the less supportive the respondents are of income redistribution (elasticity -0.1). Those who experienced severe hardships with the recent crisis tend to support redistribution more than those who had little problems or not at all (elasticity 0.13).

Furthermore, the role of preferences towards uncertainty is confirmed: the higher the (self-reported) willingness to take risks, the less likely the individual is to support or favor redistribution. Respondents with tertiary education are less inclined to support redistribution of income from the rich to the poor, compared to those with secondary education (elasticity is -0.4). Having a successful experience with business start-ups also decreases demand for income redistribution from the rich to the poor (elasticity -0.3). Those living in rural areas are more in favor of redistribution compared to metropolitan areas, while living in urban areas shows the same level of support for redistribution as those living in metropolitan areas. In each of these cases, it appears that those who would benefit the most from redistribution favor it more than those who view it as coming at their expense, or possible expense in the future.

Beliefs regarding the origins of success and poverty are also shown to be statistically significant and negative, as predicted: those who believe effort and hard work or intelligence and skills are the major factors for success are less supportive of income redistribution (elasticity -0.16). Those who consider laziness and lack of will power the major factors for people’s lack of success are also, consistently, less supportive of redistribution (elasticity -0.2).

It also turns out that better democratic institutions are correlated with a higher demand for redistribution. The result is robust across the measures used, i.e. it does not seem to depend on the particular measure used. The size of the effect is quite pronounced: a one standard deviation increase in the democracy measure increases demand for redistribution from 16 percentage points, when the voice and accountability measure is used, to 33 and 36 percentage points when controls of the executives and democracy index are used.

Furthermore, the better the governance institutions, as measured by the rule of law and control of corruption indexes, the higher is the demand for redistribution. However, the result is not robust to the various measures used. Government effectiveness appears to be insignificant (though with a positive direction), and the regulatory quality measure is insignificant but with a negative direction. The size of the effects is again quite pronounced. A one standard deviation increase in the rule of law measure increases demand for redistribution by 17 percentage points, and a one standard deviation increase in the control of corruption measure increases demand for redistribution by 27 percentage points.

The higher the level of inequality, the larger is the demand for redistribution as might be expected. This result is robust across all measures used. The size of the effect varies from 16 to 18 percentage points in response to a one standard deviation increase.

A regression analysis of preferences towards indirect redistribution also shows that self-interest motives are very pronounced, but there are traces of social preferences as well. In particular, younger people (age 18-24) would like to have more subsidized education and housing at the expense of healthcare and pensions in comparison with the age 35-44 reference group. Those in the age 25-34 group would like to redistribute public spending to housing and environment at the expense of education, pensions and public infrastructure. Respondents in the age 45-54 group would also like to redistribute additional spending from education but to pensions. The two groups of older people (age 55-64 and 65+) would like to shift extra spending from education and housing to healthcare and pensions. The group of age 65+ would also like to shift money from assistance to the poor.

Respondents with tertiary education (in comparison with holders of a secondary degree) favor extra spending for education, environment and public infrastructure at the expense of healthcare, pensions and assisting to the poor, thus revealing additional elements of social motivations. Respondents with primary education, when compared to holders of secondary degree, would like to redistribute public money from education to pensions and assistance to the poor. Respondents with poor health favor additional spending on healthcare and pensions at the expense of education.

High skilled (in terms of occupational groups) respondents would like to redistribute public money from pensions to education. Those with market relevant experience of being successful in setting up a business tend to support education and public infrastructure at the expense of housing and pensions, though the result lack statistical power.

Respondents from households with higher income support extra spending for education, environment and public infrastructure at the expense of healthcare, pensions and assistance to the poor; again pointing to the other elements of possible social motivations. Those with a self-reported positive past trend in income position tend to support spending extra money on the environment at the expense of assistance to the poor (the latter lacks statistical power). If the respondent lives in its own house or apartment, s/he tends to support redistribution from housing and assistance to the poor, to healthcare and pensions.

Respondents whose households were strongly affected by the crisis would like expenditure on environment and public infrastructure to be reduced. Those with higher self-reported willingness to take risks would redistribute extra public money to education at the expense of healthcare and housing.

Respondents who believe that success in life is mainly due to effort and hard work, intelligence and skills favor education at the expense of assistance to the poor and public infrastructure, suggesting they might view education as the key to escape poverty. Those who think that laziness and lack of willpower are the main factors behind poverty would, unsurprisingly, redistribute extra public money from assistance to the poor to healthcare.

Males (as compared to females) favor extra spending on education, housing, environment and public infrastructure at the expense of healthcare. The self-employed favor extra spending of public money to pensions at the expense of housing. There is no difference across respondents living in metropolitan, rural or urban locations.

A regression analysis shows that better democratic institutions are correlated with higher support for allocation of additional public spending to education and healthcare, environment and public infrastructure. The effects are larger for education and healthcare: one standard deviation in the democracy index increases the support for spending money on education by 3 percentage points, for healthcare by 3.1 percentage points, and only by 0.4 and 0.6 percentage points for environment and public infrastructure, respectively. This reallocation is at the expense of assistance to the poor (3.5 percentage points), housing (2.6 percentage points) and pensions (1.1 percentage points). The pattern is robust to the measure of democratic institutions used, though the marginal effects vary slightly depending on the measure.

The influence of governance institutions is similar. Respondents in countries with better governance institutions favor allocation of extra public money to education (3.2 percentage points in response to one standard deviation in government effectiveness), health care (2.9 percentage points), environment (0.9 percentage points) and public infrastructure (0.6 percentage points). The reallocation is at the expense of assistance to the poor (4.2 percentage points), housing (3.3 percentage points) and pensions (0.2 percentage points). The pattern is also robust to the measure of governance institutions with the marginal effects varying slightly depending on the measure.

The higher the level of inequality in a country, the higher the demand for spending extra public money for education at the expense of assistance to the poor, pensions and public infrastructure. A one standard deviation increase in the index, increases demand for spending extra public money on education by 3.8 percentage points, and decreases spending on assistance to the poor by 2 percentage points, pensions by 1.9 percentage points, and public infrastructure by 0.06 percentage points. The results are robust to the inequality measure used.

Overall, the analysis provides empirical evidence that transitional countries are not homogeneous with respect to preferences for redistribution, with sizeable variations in country averages and in public preferences. The study of individual determinants of preferences for redistribution confirms a dominant role of self-interest, with some indications of social sentiments as well. In addition to the usual measures used in individual level analysis, these data allow better control for both positive and negative personal and household experience. The study of institutional determinants also confirms the role of income inequality in shaping public attitudes. In particular, higher inequality is confirmed to increase the demand for direct income redistribution. A novel motive of the paper is the influence of democracy and governance institutions on demand for redistribution. Better democracy and governance institutions are likely to stimulate demand for income redistribution, revealing both higher societal demand for redistribution and appreciation of the potential capability of the government to implement redistribution effectively.

The study of individual determinants of indirect demand for redistribution adds to the overall picture and confirms not only the self-interest motives but also social preferences especially pronounced among people with tertiary education and in high income groups. Better democratic and governance institutions stimulate redistribution of public money towards education, healthcare, environment and public infrastructure, while weaker democratic and governance institutions increases demand for allocation of public money to assistance to the poor, housing and pensions.


Meltzer, A., Richards, S., 1981. “A Rational Theory of the Size of Government”. Journal of Political Economy 1989, 914–927.

Alesina, A., Angeletos, G.M., 2005. “Fairness and Redistribution”. The American Economic Review, 95(4), 960-98

[1] The countries covered were: Albania, Armenia, Azerbaijan, Belarus, Bosnia, Bulgaria, Croatia, Czech Republic, Estonia, FYROM, Georgia, Hungary, Kazakhstan, Kosovo, Kyrgyzstan, Latvia, Lithuania, Moldova, Mongolia, Montenegro, Poland, Romania, Russia, Serbia, Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine and Uzbekistan.

[2] The basic empirical equation to study individual determinants of public preferences towards income redistribution is the OLS with country fixed effects (for direct redistribution) and multinomial regression with country fixed effects (for indirect measures). When studying the influence of institutions, the equations are transformed to replace country fixed effects with an institutional measure (one at a time). To control for the basic economic differences, average GDP per capita was included.